Data-based credit generation and exchange management system based on device charging behavior

Abstract

The application discloses a data-based integral generation and exchange management system based on equipment charging behavior, and relates to the technical field of charging management. The system comprises a data acquisition and communication module, a data processing and analysis module, an integral generation and record module, an integral exchange management module and a system management background. The application combines high-frequency charging behavior with a multi-dimensional integral rule model, realizes intelligent guidance of user habits, and significantly improves user stickiness and system operation efficiency.

Description

Technical Field

[0001] This invention relates to the field of charging management technology, specifically providing a data-driven points generation and redemption management system based on device charging behavior. Background Technology

[0002] Existing points generation and redemption management systems generally suffer from passive user participation, limited points acquisition channels, and weak correlation with actual user behavior. Common points systems often rely on users' active spending, check-ins, or completion of designated tasks, resulting in rigid points generation rules that fail to effectively incentivize sustained user participation. While user charging behavior itself contains multi-dimensional data value related to time preferences, habitual patterns, and device status, current technologies have failed to effectively transform this highly engaging and regular daily behavior into sustainable user incentive resources.

[0003] The system lacks in-depth analysis and targeted incentives for continuous user behavior (such as regular charging and off-peak charging), making it difficult to guide users to form beneficial device usage habits. Therefore, there is an urgent need for a system that can deeply integrate users' high-frequency, essential behaviors, dynamically generate incentive points, and intelligently guide user behavior to improve user stickiness and system activity. Summary of the Invention

[0004] To address the aforementioned problems, the present invention proposes the following technical solution: a data-driven points generation and redemption management system based on device charging behavior, comprising:

[0005] The data acquisition and communication module is used to connect to the user's charging device or charging facility and collect raw data of charging behavior in real time. The raw data of charging behavior includes charging start time, end time, charging duration, charging amount, charging device identifier and user identifier.

[0006] The data processing and analysis module, connected to the data acquisition and communication module, is used to clean and verify the received raw charging behavior data, and to perform calculations based on a preset integral rule model. The integral rule model combines the basic value of charging power, the preset incentive period coefficient, and the continuous improvement coefficient of user charging habits.

[0007] The points generation and recording module is connected to the data processing and analysis module. It is used to generate user points with corresponding values ​​based on the calculation results output by the data processing and analysis module, and to store the points data with user identifiers in the user points database.

[0008] The points redemption management module is connected to the user points database and provides redemption interfaces including a direct redemption channel and a points lottery channel. The direct redemption channel is used to redeem points for preset physical goods, virtual benefits, or service coupons. The points lottery channel is used to receive lottery requests initiated by users, consume a fixed number of points, and provide reward results with different probabilities.

[0009] The system management backend is used to configure various parameters of the points rule model, manage redeemable items, set lottery probabilities, and manage user information.

[0010] Preferably, the calculation formula for the integral P obtained from a single charging behavior in the preset integral rule model of the data processing and analysis module is: P = B×T×C; where B is the basic integral coefficient based on the charging amount, T is the time period coefficient based on the preset incentive period to which the charging time belongs, and C is the continuous improvement coefficient of user charging habits.

[0011] Preferably, the method for determining the continuous improvement coefficient C of user charging habits includes: analyzing the user's historical charging data, and if it is identified that the user's current charging behavior has continuously improved in a preset encouragement direction compared to historical habits, then assigning a coefficient value greater than 1, wherein the encouragement direction includes the proportion of switching from non-preset incentive periods to incentive periods or shortening excessively long charging times.

[0012] Preferably, the points redemption management module is also connected to a third-party service platform interface, which is used to convert user points into virtual rights or deductions on the third-party service platform.

[0013] Preferably, the data processing and analysis module is also used to generate a group charging behavior analysis report after de-identifying the user charging behavior data, and the system management backend can dynamically adjust the parameters of the points rule model according to the analysis report.

[0014] Preferably, the system also includes a points donation and carbon credit conversion submodule, whereby users can choose to donate some or all of their points to public welfare projects, or convert them into carbon credits that represent their contribution to carbon emission reduction according to a preset ratio.

[0015] The beneficial effects of this invention are:

[0016] This invention significantly enhances user engagement and stickiness in the points system by deeply integrating users' high-frequency, essential charging behaviors. Through the design of multi-dimensional points rules (such as electricity consumption, time of day, and habit improvement), the system can intelligently and personally incentivize users to develop better charging habits, achieving refined user operations and behavioral guidance. Attached Figure Description

[0017] Figure 1This is a schematic diagram of the structure of the data-driven points generation and redemption management system based on device charging behavior according to the present invention. Detailed Implementation

[0018] The present invention will be further described below with reference to embodiments. Example: Charging and Energy Storage Incentive Management Application Based on Mini Program

[0019] This embodiment provides a "charging and energy storage points" management system based on a mini-program. It converts daily charging activities into points and enables diversified use of these points.

[0020] The system is centered around a backend cloud server and uses a mini-program as the user interface. The mini-program connects to the charging device and, upon user authorization, collects raw data about the charging behavior, including: charging start time, charging end time, initial battery percentage, final battery percentage, and charging duration. This data, along with an encrypted unique user identifier, is uploaded to the backend server in real time.

[0021] The data processing and analysis module is deployed on the backend server. The preset points rule model is as follows:

[0022] The base integral coefficient B is calculated based on the "effective energy" of the charge. The formula is B = (E_end - E_start) × K, where (E_end - E_start) is the percentage increase in battery capacity during this charge (for example, if the capacity increases from 10% to 50%, then (E_end - E_start) is 40), and K is the conversion factor (for example, set to 1). To encourage good charging habits, the K value is increased to 1.2 when the initial charge capacity is between 20% and 80%.

[0023] Time period coefficient T: To guide off-peak electricity consumption, an incentive period is set (such as 23:00-5:00 the next day when the grid load is low). During this period, charging is carried out, and T=1.5; for other ordinary periods, T=1.0.

[0024] Continuous Improvement Coefficient C: The system analyzes the user's charging records for the past 7 days. If the user completes charging within the incentive period for 3 consecutive days, the C value is set to 1.2 from the 3rd day until the charging is interrupted.

[0025] Example of points calculation: User A started charging at 2:00 AM, with an initial charge of 25% and an ending charge of 90%, and has been charging during the incentive period for two consecutive days. The effective charge this time is 65%, the initial charge was within the incentive range, and it occurred during the incentive period. Points for this charge: P = [65 × 1.2] × 1.5 × 1.0 = 117 points. The points generation and recording module will add these points to User A's account.

[0026] Users access the interface provided by the points redemption management module through the mini-program.

[0027] Redeeming Goods: Users enter the "Points Mall" subpage, where various redeemable items are displayed, such as a monthly video platform card (requires 500 points) and a coffee e-voucher (requires 300 points). After the user selects an item and confirms the redemption, the system verifies the corresponding points and issues a redemption code to the user's mini-program account via the coupon platform interface.

[0028] Lucky Draw for Cash Redemption: Users enter the "Lucky Draw" subpage. Each draw costs a fixed 50 points. The prize pool is configured by the system management backend, for example: Grand Prize: 10 RMB cash red envelope (0.1% chance of winning); First Prize: 5 RMB cash red envelope (1% chance); Second Prize: 2 RMB cash red envelope (5% chance); Lucky Prize: 10 points (remaining chance). After a user initiates a draw request, the system calculates the winning results in real time. If a user wins a cash red envelope, the system will directly deposit the corresponding cash reward into the user's WeChat Wallet through the enterprise payment interface and send an account notification to the user.

[0029] Backend Management: Through the system management backend, operators can dynamically adjust the points rules (such as coefficients K and T, and the definition of incentive periods), add / remove redeemable products, configure lottery prizes and probabilities, and view data dashboards such as user activity, points generation and consumption statistics to achieve refined operation of the system.

[0030] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A data-driven points generation and redemption management system based on device charging behavior, characterized in that: include: The data acquisition and communication module is used to connect to the user's charging device or charging facility and collect raw data of charging behavior in real time. The raw data of charging behavior includes charging start time, end time, charging duration, charging amount, charging device identifier and user identifier. The data processing and analysis module, connected to the data acquisition and communication module, is used to clean and verify the received raw charging behavior data, and to perform calculations based on a preset integral rule model. The integral rule model combines the basic value of charging power, the preset incentive period coefficient, and the continuous improvement coefficient of user charging habits. The points generation and recording module is connected to the data processing and analysis module. It is used to generate user points with corresponding values ​​based on the calculation results output by the data processing and analysis module, and to store the points data with user identifiers in the user points database. The points redemption management module is connected to the user points database and provides redemption interfaces including a direct redemption channel and a points lottery channel. The direct redemption channel is used to redeem points for preset physical goods, virtual benefits, or service coupons. The points lottery channel is used to receive lottery requests initiated by users, consume a fixed number of points, and provide reward results with different probabilities. The system management backend is used to configure various parameters of the points rule model, manage redeemable items, set lottery probabilities, and manage user information.

2. The system according to claim 1, characterized in that: The data processing and analysis module has a preset integral rule model, and the formula for calculating the integral P obtained from a single charging behavior is: P = B×T×C; where B is the basic integral coefficient based on the charging amount, T is the time period coefficient based on the preset incentive period to which the charging time belongs, and C is the continuous improvement coefficient of user charging habits.

3. The system according to claim 2, characterized in that: The method for determining the continuous improvement coefficient C of user charging habits includes: analyzing the user's historical charging data; if it is identified that the user's current charging behavior has continuously improved in a preset encouragement direction compared to historical habits, then a coefficient value greater than 1 is assigned. The encouragement direction includes the proportion of charging from non-preset incentive periods to incentive periods or shortening excessively long charging times.

4. The system according to claim 1, characterized in that: The points redemption management module is also connected to a third-party service platform interface, which is used to convert user points into virtual rights or deductions on the third-party service platform.

5. The system according to claim 1, characterized in that: The data processing and analysis module is also used to desensitize user charging behavior data and generate a group charging behavior analysis report. The system management backend can dynamically adjust the parameters of the points rule model based on the analysis report.

6. The system according to claim 1, characterized in that: The system also includes a points donation and carbon credit conversion submodule, where users can choose to donate some or all of their points to public welfare projects, or convert them into carbon credits that represent their contribution to carbon emission reduction according to a preset ratio.

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